电子行业点评：384架构引领，910C蓄势待发

Investment Rating - The report maintains a "Recommended" rating for the industry [13] Core Insights - The launch of the CloudMatrix 384 marks a significant milestone for domestic AI computing power, indicating a breakthrough year for local computing capabilities [3][4] - CloudMatrix 384 demonstrates superior performance metrics compared to Nvidia's GB200 NVL72, with BF16 performance reaching 300 PFLOPS, which is 1.7 times that of GB200 [10][11] - The deployment of CloudMatrix 384 is expected to drive demand across the supply chain, benefiting companies involved in power supply, thermal management, and semiconductor manufacturing [13] Summary by Sections Product Launch and Performance - The CloudMatrix 384, featuring 384 Ascend 910C chips, has been officially launched, showcasing a significant performance upgrade in AI model training and inference capabilities [4][6] - In a model training scenario, the CloudMatrix 384 achieved an iteration speed 1.8 times faster than the H100 cluster, highlighting its efficiency in handling large-scale AI workloads [5][10] Technical Specifications - The Ascend 910C chip integrates 53 billion transistors and supports mixed-precision computing, achieving a die-to-die bandwidth of 500GB/s [6] - The system architecture has been optimized for large-scale clusters, utilizing a flat topology to reduce latency and enhance interconnectivity among GPUs [7][8] Market Implications - The successful commercial deployment of CloudMatrix 384 is anticipated to provide a foundation for CSP manufacturers and accelerate the scaling of AI infrastructure [5][13] - The report suggests monitoring specific companies within the supply chain, including semiconductor manufacturers and thermal management firms, as they are likely to benefit from increased demand due to the deployment of CloudMatrix 384 [13]